2016 International Conference on Big Data and Smart Computing (BigComp) (2016)
Hong Kong, China
Jan. 18, 2016 to Jan. 20, 2016
Mingzhao Li , RMIT University, Melbourne, Australia 3000
Zhifeng Bao , RMIT University, Melbourne, Australia 3000
Liangjun Song , RMIT University, Melbourne, Australia 3000
Henry Duh , University of Tasmania, Launceston, Australia 7250
The popularity of social media has generated an abundance of publicly available data about tourist behaviour. We aim to exploit this to provide a snapshot of customized routes for pre-trip tourists and help the tourism industry understand the real behaviour of tourists for better policy making. Therefore, we propose an analytic framework that is able to automatically collect, clean and integrate all forms of tourists' activity data from various social media sites, and provides an interactive yet visualized analysis to facilitate users' exploration of underlying data. Specifically, it is able to (1) support multidimensional views of tourists' trajectory data, e.g. temporally, spatially, textually, etc; (2) support multi-granularity visualization where the trajectory of either a group of tourists or a single tourist can be efficiently retrieved.
Data visualization, Media, Trajectory, Google, Visual analytics, Industries, Query processing
Mingzhao Li, Zhifeng Bao, Liangjun Song and H. Duh, "Social-aware visualized exploration of tourist behaviours," 2016 International Conference on Big Data and Smart Computing (BigComp)(BIGCOMP), Hong Kong, China, 2016, pp. 289-292.